Predicting Robotics Pedagogical Content Knowledge: The Role of Computational and Design Thinking Dispositions via Teaching Beliefs

IF 4 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Journal of Educational Computing Research Pub Date : 2024-02-29 DOI:10.1177/07356331241236882
Chung-Yuan Hsu, Meng-Jung Tsai
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Abstract

This research aimed to investigate the structural relationships among teachers’ computational thinking (CT), design thinking (DT), robotics teaching beliefs, and robotics pedagogical content knowledge (RPCK). A total of 98 in-service and pre-service teachers who participated in a robotics teaching professional development workshop served as the sample of the study. A survey including the Computational Thinking Scale, the Design Thinking Disposition Scale, the Robotics Teaching Beliefs Scale and the Technological Pedagogical Content Knowledge–Robotics Scale was conducted after the workshop. A confirmatory factor analysis was employed to validate the measurement constructs, and Partial Least Squares - Structural Equation Modeling (PLS-SEM) analysis was utilized to examine the relationships among the factors. The results revealed that both CT and DT dispositions could positively predict teachers’ robotics teaching beliefs, which subsequently predicted their RPCK. Moreover, a direct positive relationship between CT and RPCK was identified, while such a relationship was not evident for DT. The model demonstrates the critical role of CT in shaping teachers' beliefs and pedagogical strategies of robotics teaching, and provides insights into the indirect influence of DT. Finally, the Model of Robotics Teaching Professional Development (MRTPD) was proposed to profile how to promote teachers’ pedagogical content knowledge of robotics teaching from their CT and DT dispositions.
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预测机器人教学内容知识:通过教学信念看计算和设计思维处置的作用
本研究旨在探讨教师的计算思维(CT)、设计思维(DT)、机器人教学信念和机器人教学内容知识(RPCK)之间的结构关系。参加机器人教学专业发展研讨会的在职和职前教师共 98 人作为研究样本。工作坊结束后进行了一项调查,包括计算思维量表、设计思维倾向量表、机器人教学信念量表和技术教学内容知识--机器人量表。研究采用了确认性因子分析来验证测量建构,并利用偏最小二乘法-结构方程建模(PLS-SEM)分析来研究各因子之间的关系。结果显示,CT 和 DT 两种处置方式都能正向预测教师的机器人教学信念,进而预测教师的 RPCK。此外,CT 和 RPCK 之间存在直接的正相关关系,而 DT 则不存在这种关系。该模型证明了 CT 在塑造教师机器人教学信念和教学策略方面的关键作用,并为 DT 的间接影响提供了启示。最后,提出了机器人教学专业发展模型(MRTPD),以剖析如何从教师的CT和DT处置出发,促进教师对机器人教学内容知识的掌握。
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来源期刊
Journal of Educational Computing Research
Journal of Educational Computing Research EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
11.90
自引率
6.20%
发文量
69
期刊介绍: The goal of this Journal is to provide an international scholarly publication forum for peer-reviewed interdisciplinary research into the applications, effects, and implications of computer-based education. The Journal features articles useful for practitioners and theorists alike. The terms "education" and "computing" are viewed broadly. “Education” refers to the use of computer-based technologies at all levels of the formal education system, business and industry, home-schooling, lifelong learning, and unintentional learning environments. “Computing” refers to all forms of computer applications and innovations - both hardware and software. For example, this could range from mobile and ubiquitous computing to immersive 3D simulations and games to computing-enhanced virtual learning environments.
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